Parathyroid Hormone Administration Improves Bone Marrow Microenvironment and Partially Rescues Haematopoietic Defects in Bmi1-Null Mice
Bibliographic record
Abstract
The epigenetic regulator Bmi1 is key in haematopoietic stem cells, and its inactivation leads to defects in haematopoiesis. Parathyroid hormone (PTH), an important modulator of bone homeostasis, also regulates haematopoiesis, so we asked whether PTH administration improves bone marrow microenvironment and rescues the haematopoietic defects in Bmi1-null mice. The mice were treated with PTH1-34 (containing the first 34 residues of mature PTH), an anabolic drug currently used for treating osteoporosis, and compared with the vehicle-treated Bmi1-/- and wild-type littermates in terms of skeletal and haematopoietic phenotypes. We found that the administration significantly increased all parameters related to osteoblastic bone formation and significantly reduced the adipocyte number and PPARγ expression. The bone marrow cellularity, numbers of haematopoietic progenitors and stem cells in the femur, and numbers of lymphocytes and other white blood cells in the peripheral blood all increased significantly when compared to vehicle-treated Bmi1-/- mice. Moreover, the number of Jagged1-positive cells and percentage of Notch intracellular domain-positive bone marrow cells and protein expression levels of Jagged1 and NICD in bone tissue were also increased in Bmi1-/- mice upon PTH1-34 administration,whereas the up-regulation of PTH on both Notch1 and Jagged1 gene expression was blocked by the Notch inhibitor DAPT administration. These results thus indicate that PTH administration activates the notch pathway and partially rescues haematopoietic defects in Bmi1-null mice, further suggesting that haematopoietic defects in the animals are not only a result of reduced self-renewal of haematopoietic stem cells but also due to impaired bone marrow microenvironment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".